AIMC Topic: Neural Networks, Computer

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A Comparison of Machine Learning Algorithms and Feature Sets for Automatic Vocal Emotion Recognition in Speech.

Sensors (Basel, Switzerland)
Vocal emotion recognition (VER) in natural speech, often referred to as speech emotion recognition (SER), remains challenging for both humans and computers. Applied fields including clinical diagnosis and intervention, social interaction research or ...

EnsembleSplice: ensemble deep learning model for splice site prediction.

BMC bioinformatics
BACKGROUND: Identifying splice site regions is an important step in the genomic DNA sequencing pipelines of biomedical and pharmaceutical research. Within this research purview, efficient and accurate splice site detection is highly desirable, and a ...

Guiding principle of reservoir computing based on "small-world" network.

Scientific reports
Reservoir computing is a computational framework of recurrent neural networks and is gaining attentions because of its drastically simplified training process. For a given task to solve, however, the methodology has not yet been established how to co...

Method for Quantum Denoisers Using Convolutional Neural Network.

Computational intelligence and neuroscience
In many applications of quantum information science, high-dimensional entanglement is needed. Quantum teleportation is used for transferring information from one place to another using Einstein-Podolsk-Rosen pairs (EPR) and two classical bits of comm...

Photovoltaic Power Generation Forecasting Using a Novel Hybrid Intelligent Model in Smart Grid.

Computational intelligence and neuroscience
The exponential growth of electrical demand and the integration of renewable energy sources (RES) brought new challenges in the traditional grid about energy quality. The transition from traditional grid to smart grid is the best solution which provi...

A Multimodel-Based Deep Learning Framework for Short Text Multiclass Classification with the Imbalanced and Extremely Small Data Set.

Computational intelligence and neuroscience
Text classification plays an important role in many practical applications. In the real world, there are extremely small datasets. Most existing methods adopt pretrained neural network models to handle this kind of dataset. However, these methods are...

HIT HAR: Human Image Threshing Machine for Human Activity Recognition Using Deep Learning Models.

Computational intelligence and neuroscience
In recent days, research in human activity recognition (HAR) has played a significant role in healthcare systems. The accurate activity classification results from the HAR enhance the performance of the healthcare system with broad applications. HAR ...

MHA-Net: A Multibranch Hybrid Attention Network for Medical Image Segmentation.

Computational and mathematical methods in medicine
The robust segmentation of organs from the medical image is the key technique in medical image analysis for disease diagnosis. U-Net is a robust structure for medical image segmentation. However, U-Net adopts consecutive downsampling encoders to capt...

Rulkov neural network coupled with discrete memristors.

Network (Bristol, England)
The features of memristive-coupled neural networks have been studied extensively in the continuous field. However, the particularities of the discrete domain are rarely mentioned. This paper constructs a discrete memristor with sine-type conductance ...

Practical synchronization of neural networks with delayed impulses and external disturbance via hybrid control.

Neural networks : the official journal of the International Neural Network Society
This paper studies the problem of practical synchronization for delayed neural networks via hybrid-driven impulsive control in which delayed impulses and external disturbance are taken into account. Firstly, a switching method which establishes the r...